Convergence Analysis of Volumetric Stretch Energy Minimization and Its Associated Optimal Mass Transport

被引:0
|
作者
Huang, Tsung-Ming [1 ]
Liao, Wei-Hung [2 ]
Lin, Wen-Wei [3 ]
Yueh, Mei-Heng [1 ]
Yau, Shing-Tung [4 ,5 ]
机构
[1] Natl Taiwan Normal Univ, Dept Math, Taipei 116, Taiwan
[2] Natl Yang Ming Chiao Tung Univ, Dept Appl Math, Hsinchu 300, Taiwan
[3] Nanjing Ctr Appl Math, Nanjing 211135, Peoples R China
[4] Natl Yang Ming Chiao Tung Univ, Dept Appl Math, Hsinchu 300, Taiwan
[5] Tsinghua Univ, Yau Math Sci Ctr, Beijing 100084, Peoples R China
来源
SIAM JOURNAL ON IMAGING SCIENCES | 2023年 / 16卷 / 03期
关键词
volume-/mass-preserving parameterization; optimal mass transport; R-linear convergence; projected gradient method; Nesterov-based acceleration; O(1/m) convergence; O(1/m2) convergence; EARTH MOVERS DISTANCE; ALGORITHM;
D O I
10.1137/22M1528756
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Volumetric stretch energy has been widely applied to the computation of volume-/mass-preserving parameterizations of simply connected tetrahedral mesh models M. However, this approach still lacks theoretical support. In this paper, we provide a theoretical foundation for volumetric stretch energy minimization (VSEM) to show that a map is a precise volume-/mass-preserving parameter-ization from M to a region of a specified shape if and only if its volumetric stretch energy reaches 32\mu(M), where \mu(M) is the total mass of M. We use VSEM to compute an \bfitvarepsilon -volume-/mass-preserving map f\ast from M to a unit ball, where \bfitvarepsilon is the gap between the energy of f\ast and 32\mu(M). In addition, we prove the efficiency of the VSEM algorithm with guaranteed asymptotic R-linear convergence. Furthermore, based on the VSEM algorithm, we propose a projected gradient method for the computation of the \bfitvarepsilon -volume-/mass-preserving optimal mass transport map with a guaran-teed convergence rate of O(1/m), and combined with Nesterov-based acceleration, the guaranteed convergence rate becomes O(1/m2). Numerical experiments are presented to justify the theoret-ical convergence behavior for various examples drawn from known benchmark models. Moreover, these numerical experiments show the effectiveness of the proposed algorithm, particularly in the processing of 3D medical MRI brain images.
引用
收藏
页码:1825 / 1855
页数:31
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